@article {Almansa:2014:0035-9254:85,
title = "A factor mixture model for multivariate survival data: an application to the analysis of lifetime mental disorders",
journal = "Journal of the Royal Statistical Society: Series C (Applied Statistics)",
parent_itemid = "infobike://bpl/rssc",
publishercode ="bp",
year = "2014",
volume = "63",
number = "1",
publication date ="2014-01-01T00:00:00",
pages = "85-102",
itemtype = "ARTICLE",
issn = "0035-9254",
eissn = "1467-9876",
url = "https://www.ingentaconnect.com/content/bpl/rssc/2014/00000063/00000001/art00005",
doi = "doi:10.1111/rssc.12026",
keyword = "Item response theory, Cure fraction, Latent classes, Psychiatric comorbidity, Internalizing disorders, Disorder diathesis",
author = "Almansa, Josu{\’e} and Vermunt, Jeroen K. and Forero, Carlos G. and Alonso, Jordi and European Study of the Epidemiology of Mental Disorders Mental Health Disability: a European Assessment in the Year 2000 Investigatorsrssc12026-cr-0005",
abstract = "The assessment of the lifetime prevalence of mental disorders under comorbidity conditions is an important area in mental health research. Because information on lifetime disorders is usually gathered retrospectively within crosssectional studies, the information is necessarily
right censored and this should be taken into account when setting up models for the estimation of lifetime prevalences. We propose a factor analytic discrete time survival model combining mixture item response theory and discrete time hazard functions to describe disorder associations while
accounting for censoring. This model is used for describing the lifetime prevalence and comorbidity of eight depression and anxiety disorders from the European Study of the Epidemiology of Mental Disorders.",
}